@aws-sdk/client-dynamodb
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AWS SDK for JavaScript Dynamodb Client for Node.js, Browser and React Native
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TypeScript
import { DynamoDBClientResolvedConfig, ServiceInputTypes, ServiceOutputTypes } from "../DynamoDBClient";
import { BatchWriteItemInput, BatchWriteItemOutput } from "../models/models_0";
import { Command as $Command } from "@aws-sdk/smithy-client";
import { Handler, MiddlewareStack, HttpHandlerOptions as __HttpHandlerOptions, MetadataBearer as __MetadataBearer } from "@aws-sdk/types";
export declare type BatchWriteItemCommandInput = BatchWriteItemInput;
export declare type BatchWriteItemCommandOutput = BatchWriteItemOutput & __MetadataBearer;
/**
* <p>The <code>BatchWriteItem</code> operation puts or deletes multiple items in one or more
* tables. A single call to <code>BatchWriteItem</code> can write up to 16 MB of data,
* which can comprise as many as 25 put or delete requests. Individual items to be written
* can be as large as 400 KB.</p>
* <note>
* <p>
* <code>BatchWriteItem</code> cannot update items. To update items, use the <code>UpdateItem</code>
* action.</p>
* </note>
* <p>The individual <code>PutItem</code> and <code>DeleteItem</code> operations specified in
* <code>BatchWriteItem</code> are atomic; however <code>BatchWriteItem</code> as a whole is not. If any
* requested operations fail because the table's provisioned throughput is exceeded or an
* internal processing failure occurs, the failed operations are returned in the
* <code>UnprocessedItems</code> response parameter. You can investigate and optionally resend the
* requests. Typically, you would call <code>BatchWriteItem</code> in a loop. Each iteration would
* check for unprocessed items and submit a new <code>BatchWriteItem</code> request with those
* unprocessed items until all items have been processed.</p>
* <p>If <i>none</i> of the items can be processed due to insufficient
* provisioned throughput on all of the tables in the request, then
* <code>BatchWriteItem</code> returns a
* <code>ProvisionedThroughputExceededException</code>.</p>
* <important>
* <p>If DynamoDB returns any unprocessed items, you should retry the batch operation on those
* items. However, <i>we strongly recommend that you use an exponential backoff algorithm</i>.
* If you retry the batch operation immediately, the underlying read or write requests can
* still fail due to throttling on the individual tables. If you delay the batch operation
* using exponential backoff, the individual requests in the batch are much more likely to
* succeed.</p>
* <p>For more information, see <a href="https://docs.aws.amazon.com/amazondynamodb/latest/developerguide/ErrorHandling.html#Programming.Errors.BatchOperations">Batch Operations and Error Handling</a> in the <i>Amazon DynamoDB
* Developer Guide</i>.</p>
* </important>
*
* <p>With <code>BatchWriteItem</code>, you can efficiently write or delete large amounts of
* data, such as from Amazon EMR, or copy data from another database into DynamoDB. In
* order to improve performance with these large-scale operations,
* <code>BatchWriteItem</code> does not behave in the same way as individual
* <code>PutItem</code> and <code>DeleteItem</code> calls would. For example, you
* cannot specify conditions on individual put and delete requests, and
* <code>BatchWriteItem</code> does not return deleted items in the response.</p>
* <p>If you use a programming language that supports concurrency, you can use
* threads to write items in parallel. Your application must include the necessary logic to
* manage the threads. With languages that don't support threading, you must update
* or delete the specified items one at a time. In both situations, <code>BatchWriteItem</code>
* performs the specified put and delete operations in
* parallel, giving you the power of the thread pool approach without having to introduce
* complexity into your application.</p>
* <p>Parallel processing reduces latency, but each specified put and delete request consumes the same number of write capacity units whether it is processed in parallel or not. Delete operations on nonexistent items consume one write capacity unit.</p>
* <p>If one or more of the following is true, DynamoDB rejects the entire batch write operation:</p>
* <ul>
* <li>
* <p>One or more tables specified in the <code>BatchWriteItem</code> request does not exist.</p>
* </li>
* <li>
* <p>Primary key attributes specified on an item in the request do not match those in the corresponding table's primary key schema.</p>
* </li>
* <li>
* <p>You try to perform multiple operations on the same item in the same <code>BatchWriteItem</code>
* request. For example, you cannot put and delete the same item in the same
* <code>BatchWriteItem</code> request. </p>
* </li>
* <li>
* <p>
* Your request contains at least two items with identical hash and range keys (which essentially is two put operations).
* </p>
* </li>
* <li>
* <p>There are more than 25 requests in the batch.</p>
* </li>
* <li>
* <p>Any individual item in a batch exceeds 400 KB.</p>
* </li>
* <li>
* <p>The total request size exceeds 16 MB.</p>
* </li>
* </ul>
*/
export declare class BatchWriteItemCommand extends $Command<BatchWriteItemCommandInput, BatchWriteItemCommandOutput, DynamoDBClientResolvedConfig> {
readonly input: BatchWriteItemCommandInput;
constructor(input: BatchWriteItemCommandInput);
/**
* @internal
*/
resolveMiddleware(clientStack: MiddlewareStack<ServiceInputTypes, ServiceOutputTypes>, configuration: DynamoDBClientResolvedConfig, options?: __HttpHandlerOptions): Handler<BatchWriteItemCommandInput, BatchWriteItemCommandOutput>;
private serialize;
private deserialize;
}